Clustering belongs to the set of mathematical problems which aim at classification of data or objects into related sets or classes. Many different pattern clustering approaches bas...
Faezeh Ensan, Mohammad Hossien Yaghmaee, Ebrahim B...
We propose two Euclidean minimum spanning tree based clustering algorithms — one a k-constrained, and the other an unconstrained algorithm. Our k-constrained clustering algorith...
This paper presents a minimum area, low-power driven clustering algorithm for coarse-grained, antifuse-based FPGAs under delay constraints. The algorithm accurately predicts logic...
– Clustering is a standard approach for achieving efficient and scalable performance in wireless sensor networks. Most of the published clustering algorithms strive to generate t...
Adel M. Youssef, Mohamed F. Younis, Moustafa Youss...
Detecting densely connected subgroups in graphs such as communities in social networks is of interest in many research fields. Several methods have been developed to find commun...
Abstract. Clustering algorithms for multidimensional numerical data must overcome special difficulties due to the irregularities of data distribution. We present a clustering algo...
Representative-based clustering algorithms are quite popular due to their relative high speed and because of their sound theoretical foundation. On the other hand, the clusters the...
In this paper a fuzzy quantization dequantization criterion is used to propose an evaluation technique to determine the appropriate clustering algorithm suitable for a particular ...
We present an evolutionary clustering method which can be applied to multi-relational knowledge bases storing resource annotations expressed in the standard languages for the Sema...
Abstract. This paper illustrates how the Quadratic Assignment Problem (QAP) is used as a mathematical model that helps to produce a visualization of microarray data, based on the r...
Mario Inostroza-Ponta, Alexandre Mendes, Regina Be...